Efficient power and admission control in multi-cell cognitive radio networks employing hybrid users

Abstract

A recent class of cognitive user that can emerge and change the future of cognitive radio networks (CRNs) is hybrid user (HU). HU is an advanced primary user that is armed with cognitive functions to benefit greatly from CRN. In this paper, we aim to propose a framework to employ this type of users in CRNs. In this regard, we introduce a modified multi-cell CRN (MMCRN) based on HUs. In conventional MCRN (CMCRN), each user connects to its own base station (BS); however, in MMCRN, it is possible for HUs to exploit the secondary network. To construct the MMCRN, a BS assignment algorithm is proposed to assign the HUs to proper BSs. Afterwards, in an infeasible MMCRN, the problem of maximizing the number of admitted SUs is studied and a novel algorithm is presented. Furthermore, sum-throughput maximization of SUs is investigated in a feasible MMCRN. Finally, we modify our schemes considering channel gain uncertainty and propose algorithms that are robust against channel gain fluctuation. It is theoretically presented that our proposed schemes can significantly improve the efficiency of the network. The extensive simulations also verify the superior efficiency of MMCRN compared to CMCRN.